Recent studies have suggested that the respiratory central pattern generator (RCPG) can solve complex dynamic optimization problems in regulating the respiratory motor output in response to phasic chemo- or mechano-afferent inputs. Such optimization behavior is reminiscent of operant conditioning, an innate animal behavior where the expected payoff is adaptively optimized through positive and negative feedback reinforcement of behavior. The purpose of this research is to investigate the role of operant conditioning in engendering respiratory optimization in a spontaneously breathing animal model. The specific aims are to examine the roles of 1) vagal volume feedback, 2) carotid chemoreceptor feedback, and 3) combined chemo- and mechano-afferent feedback in operant conditioning of RCPG output. These afferent pathways will be physically stimulated by electrical or mechanical means in synchrony with the central respiratory rhythm in anesthetized, paralyzed and servo-ventilated rabbits. The effects of temporal correlations of neural activities on the conditioning behavior will be examined by pairing the afferent and efferent activities at varying phase shifts. The phasic inputs are designed to "train" the respiratory neural network to adapt to altered physiological inputs. The relation of the adaptive response to the optimization of the amplitude and wave shape of the central respiratory pattern will be examined by using a mathematical model developed previously. These in-vivo electrophysiological data will complement other electrophysiological studies using in-vitro techniques as well as neural network modeling of the respiratory control system currently under way.